Implement Dendritic Cell Algorithm (DCA)

[Joao-Paulo-Silva]

Objective

This issue aims to add a new module to AISP, dedicated to algorithms based on Danger Theory, starting with the implementation of Dendritic Cell Algorithm (DCA).

Details

The new module, named DTA (Danger Theory Algorithms). This first component willl be the DCA, which applies the principples of Danger Theory to anomaly detection and classification task.

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Proposed Structure:

aisp/
  └─ dta/
     ├─ tests/
     ├─ __init__.py
     └─ _dendritic_cell_algorithm.py

Important
Assess the feasibility of implememting the algorithm for multiclass probllems, taking into account the approaches used in algorithms implemented in AISP, such as RNSA and BNSA or KNN for predict.

References

Below are some key references to support the implementation of technique:

• BRABAZON, Anthony; O’NEILL, Michael; MCGARRAGHY, Seán. Natural Computing Algorithms. Springer Berlin Heidelberg, 2015. Pag. 315-319 DOI: 10.1007/978-3-662-43631-8
• BROWNLEE, Jason. Dendritic Cell Algorithm. Clever Algorithms, 2011. Available at: https://cleveralgorithms.com/nature-inspired/immune/dca.html